##
* *Reflection: Student Grouping
One-Variable Distribution Activity - Section 2: Comparing Quantitative Data Activity

Choosing student groups for an open ended project of this type can be tricky. Besides considering skill level, individual personalities, compatible work habits, and artistic skill, this project also requires a consideration of personal interests. Students who are genuinely interested in the dataset chosen by their group will have more buy-in and ultimately more retention of the skills required for the final product. Sometimes, I find that it helps for students to jot down a couple of their own ideas first. While they are doing some preliminary independent research, I can use these ideas to sort students with like interests.

Additionally, this poster task is easily compartmentalized (create comparative boxplots, stemplots, histograms, verbally compare and contrast these measures, and make an artistic display). This compartmentalization makes fair division of labor easier than usual. Because of this, I find that it makes a good opportunity to try out some student groupings that we haven’t yet experienced.

*Choosing Student Groups*

*Student Grouping: Choosing Student Groups*

# One-Variable Distribution Activity

Lesson 4 of 13

## Objective: SWBAT use the internet to identify a one-variable data set, make a graph of the data set, calculate summary statistics for the data set, and write a paragraph to describe the distribution.

## Big Idea: Graphs and summary statistics help us communicate the most important features of one-variable data sets.

*90 minutes*

#### Warm-Up

*15 min*

In today's lesson, students will identify their own single variable data sets to describe. The warm up is designed to spark their curiosity about distributions so that they are inspired to choose an interesting data set.

I select a few data sets that students might be interested in and ask them to predict various aspects of the data set. For example, I might ask about the mean, standard deviation, or shape of the following distributions:

- CEO salaries
- batting averages of Boston Red Sox players
- age of teachers at our school
- ages of people in our town
- college tuitions

When possible, I show them the actual distributions and answer the questions I've asked. In other cases, we have to speculate (as in the ages of people in our town).

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For today's activity, my students will work in mixed groups of 3 to identify quantitative data sets, compare them, and make a poster to explain their findings to their classmates. I choose the groups for this activity by thinking about who works well together and who needs support. I also try to assign at least one person with strong art skills to each group so that they can lead the creative process.

When students are seated with their groups, I invite one person from each group to visit the supply closet for small poster boards and markers and another student to get a laptop from the cart. While they get settled, I distribute One-Variable Data Activity, which has directions for the poster activity along with a scoring rubric.

Students will use most of the period to select, organize, and present their data. This activity is great for reinforcing MP2, MP4 and MP5 because students need to create a coherent representation of two data sets using technology and then interpret their results.

#### Resources

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#### Wrap-Up

*10 min*

As students complete their posters, they pin them up on the bulletin board and return their supplies to the closet. When all groups have done this, we take a few minutes to debrief the process. We discuss challenging aspects of the process and look at the group's results. If any group of students wants a bit more time to finish their poster, they can take it home and submit it first thing in the morning.

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- LESSON 1: Introduction to Statistics
- LESSON 2: Looking at One-Variable Data Sets
- LESSON 3: Describing Single-Variable Data Sets
- LESSON 4: One-Variable Distribution Activity
- LESSON 5: Bell-Shaped Distributions and the Normal Model
- LESSON 6: Quiz on Distributions and the Empirical Rule
- LESSON 7: Using Technology with Normal Model
- LESSON 8: Assessing Statistical Significance DAY 1
- LESSON 9: Assessing Statistical Significance DAY 2
- LESSON 10: Developing Confidence Intervals DAY 1
- LESSON 11: Developing Confidence Intervals DAY 2
- LESSON 12: Review of One-Variable Statistics
- LESSON 13: Unit Assessment: One-Variable Statistics